1. e-Science and us Peter Robinson ITSEE, University of Birmingham

2. Making bets Some that paid off: the web, google Some that have not: automatic author identification, metadata (compare: full text searching), semantic web

3. Technology Hype Cycle n Devised by Jackie Fenn, analyst, © Gartner Group

4. What e-Science does best

5. Types of Grid (1) n Computational Grids u CPU resources from different platforms are utilised to address a single problem F parallel workloads F distribution of serial workloads across a pool of systems u Two main types F server grids F desktop scavenging u Example: SETI n Data Grids u Sharing of Data across multiple platforms F Distributed filesystems F Federated databases (DBMS) F Data replication u Example: e- Diamond

6. Types of Grid (2) n Connecting people n “access grid” n ensemble of resources including multimedia large- format displays, presentation and interactive environments, and interfaces to Grid middleware and to visualization environments. n Used to support group-to- group interactions across the Grid. u large-scale distributed meetings u collaborative work sessions u seminars, lectures, tutorials, and training

7. The changing world of scholarly editing

8. 1658: Walton’s Polyglot Bible

9. 2006: The Digital Nestle-Aland Greek New Testament

10. The old … The edition is made by a single scholar or single scholarly group The editor determines what is presented and how it is presented The editor controls who contributes what to the edition Only the editor can alter any word of the edition — The edition is made by the reader from whatever is available — The reader determines what is read and how it is presented — The reader controls the choice of materials —Anyone can alter any word and invite others to read it …the new

11. The old … The editor chooses the text to edit The editor gathers the materials (digital photographs, etc) The editor transcribes them The editor collates them ….. — Libraries publish digital images online free for everyone — Anyone transcribes them —Anyone collates them The editor analyzes the collation and makes the text —Anyone analyzes the collation and makes a text The editor publishes the edition —Everyone publishes what they can, when they can The edition is finished -- till the next editor —The edition is never finished …the new

12. What we need: one project The FourJohn project: collaborators in Munster, Birmingham, Aberdeen, Salzburg, and… Real time entry of transcripts, annotations Real time collation, analysis, republication Instant access to work of others Multi-layered, distributed, controls and validations Completely transparent to the user and the scholar

13. How e-Science can help Provide tools for data entry, analysis, publication, control We are NOT discovering ‘previously unknown things’ from existing data We ARE making new data, in forms which might enable a multitude of new uses (examples: automatic text/image alignment->scribal hand matching)

14. How e-Science can help We need: a new generation of collaborative tools We need: clear policies for data reuse and credit We need: better access to digital images

15. e-Science will not: Do our research for us Make ontologies for us Find what we do not know (but it might help retrieve what others have just said)

16. Some model projects: VOTES: collecting, managing and sharing data on clinical trials (compare: PSYGRID) SBRN: creating, sharing, enhancing research data DAME: testbed for ‘brokering’ knowledge about aircraft maintenance, to help make decisions SILCHESTER VRE: amalgamating archaeological information BVREH: Oxford research environment for the humanities ASTROGRID workbench: allowing astronomers to work together Are these too general? Or too specific?

17. What we can do next: Define what each of us wants, individually Establish what is common to all our needs Map this onto e-Science: is there a fit? If there is: move to next stage. If not: we say so. How ‘common’ are we? Can we speak persuasively for our community?